Publication Date: 2012
2025 29th International Computer Conference, Computer Society of Iran, CSICC 2025pp. 6005-6008
In this paper, a method is presented to recognition and modeling of three types of dormers from lidar data. The input data of this proposed algorithm involves raw roof lidar data, a regular grid of lidar data and an initial building model without superstructures. This proposed method is modular. The first stage provides a recognition type of dormers via a support vector machine. The second stage reconstructs the dormer models. Experiments show the efficiency of the proposed method. © 2012 IEEE.
Sattari, M.,
Shahbazi, M.,
Sattari, M.,
Homayouni, S.,
Saadatseresht, M. Publication Date: 2011
2025 29th International Computer Conference, Computer Society of Iran, CSICC 2025pp. 148-155
This paper describes a method for detecting and recognizing traffic signs by integrating the range and intensity images of a Time-of-flight camera, based on Photonic Mixer Device (PMD) technology, with images of a standard digital camera. The reflectivity of signs surfaces along with background suppression ability and active sensing of the PMD camera make the signs sharply visible in intensity images. Besides the image descriptors, utilizing the object-based information provides robust and reliable detection and recognition. The overall acquisition system and proposed technique overcome the conventional illumination, disorientation and scaling problems in detection and recognition process. The method of this paper is implemented and evaluated on data acquired by a multi-sensor mobile mapping system.
Publication Date: 2025
Land Use Policy (0264-8377)
This paper presents a method for quantitatively evaluating property landscape views by integrating Building Information Model (BIM) and 3D Geographical Information Systems (3D GIS). Previous studies have used limited methods such as dummy variables and the hedonic method, which are subjective and implicit. Additionally, GIS-based methods have not fully accounted for important variables such as building layout, observer position, and landscape diversity, all of which impact view assessment quality. To address these limitations, the proposed method integrates 3D GIS and BIM to accurately determine the field of view, while considering the observer's position in relation to windows, window size, observer field of view, landscape diversity and quality, and the simultaneous presence of visible landscapes. The weight of simultaneous presence and intensifying effects of different landscapes were modeled using Sugeno fuzzy measures and Choquet integral. An Ordered Weighted Average operator (OWA) was designed to estimate the building's view score in optimistic, normal, and pessimistic states. The proposed method was evaluated on a case study building, demonstrating its effectiveness in measuring and ranking property based on visible landscape views. Additionally, the proposed method can be applied in pre-construction and architectural design phases to identify optimal positions for windows and terraces, to enhance the aesthetic value of a building's view. © 2025 Elsevier Ltd
Maleki, J.,
Masoumi Z.,
Hakimpour F.,
Coello Coello C.A. Publication Date: 2022
Transactions in GIS (13611682)(2)
Due to the many objectives and constraints involved in urban land use planning (ULUP), this is considered as a many-objective and complex optimization problem that needs a variety of geographical analyses. In this article, the main target is improving NSGA-III as an advanced many-objective optimization algorithm for solving the ULUP problem. In this study, five objective functions (i.e., consistency, dependency, compactness, suitability, and per capita violation of land uses) are considered for their simultaneous optimization for allocation. The proposed algorithm is tested using the spatial data of region 7, district 1 of Tehran using a vector format. To evaluate the results, two more real datasets were implemented. The performance of the improved algorithm is compared concerning NSGA-II and NSGA-III in the main case study area and two other instances. The comparison results show that the improved algorithm increases the convergence and diversity of the generated solutions in ULUP concerning the results obtained by these two other algorithms. The results of the optimization with these methods can help decision-makers toward sustainable development in the construction of new cities, new towns, and smart cities. © 2021 John Wiley & Sons Ltd.
Maleki, J.,
Masoumi Z.,
Hakimpour F.,
Coello Coello C.A. Publication Date: 2020
Land Use Policy (0264-8377)
Spatial urban land-use planning is a complex process, through which we aim to allocate suitable land-uses while taking into consideration multiple and conflicting objectives and constraints under certain spatial contexts. Landowners should be modeled as players that are able to interact with each other so as to seek their best land-uses while considering multiple objectives and constraints simultaneously. Game theory provides a tool for land-use planners to model and analyze such interactions. In this paper, spatial urban land-use planning is considered as a game to model local competitions between landowners, whose players (i.e. landowners) of which play to pick the most suitable land-use for themselves. The game is defined based on the objectives of consistency, dependency, suitability, compactness of land-uses, and land-use per capita demand. In this paper, three different scenarios are designed for the players. In the first scenario, the players are greedy and only accept the most compatible land-use. In the second scenario, conversely, the players are fully collaborative and care about other players’ payoff. In the third scenario, the players are first greedy, but when they cannot achieve an agreement with other players, they change their attitude to become gradually collaborative for reaching the Nash equilibrium (NE). Furthermore, the dissatisfaction index (DI), which represents the number of unsatisfied landowners with their current land-use, is defined to compare the different scenarios. The proposed model is tested in a district located in District 7 in Tehran (the capital city of Iran) with 2710 parcels. Results of the first scenario showed that, at the beginning of the game, 50 % of the landowners were not satisfied with their current land-uses, but after 50 iterations, about 100 landowners were dissatisfied with their land-use and this scenario was not able to reach the NE. Results of the second scenario indicated that, in order to reach an optimized layout, 325 parcels needed to be changed. Also, after reaching the NE in this scenario, values of the objective functions did not significantly improve. So, lowering the expectations of the players would not lead to appropriate results. The outcomes of the third scenario provided appropriate results, which could be achieved when the expectation levels of the players could be changed during the game. Furthermore, the NE was obtained among the players and the objective functions improved by 20 % on average in comparison with the other scenarios. Moreover, results of the scenarios were compared with the optimized layout obtained by a genetic algorithm (GA) using different parameter values. Results of the comparison also revealed that the urban layouts produced by game theory improved the objective function values obtained by the GA in about 10 % and improved the GA's running time in more than 85 %, on average in this research. © 2020 Elsevier Ltd
Publication Date: 2020
Process Safety and Environmental Protection (09575820)
The urban sewer pipeline network is a vital urban infrastructure that is highly at risk of failure and its deterioration can be harmful to the environment and public health and safety. Therefore, for performing an effective rehabilitation program, it is needed to prioritize the sewer pipelines. In this paper, a novel risk assessment approach is proposed for prioritizing sewer pipelines based on a combination of Geospatial Information System (GIS) and Analytic Hierarchy Process (AHP)- Data Envelopment Analysis (DEA). To do so, it calculates the Probability of Failure (PoF), along with the Consequence of Failure (CoF) for the sewer pipelines. Bayesian Network (BN) as the probabilistic method is used to calculate PoF. The main contribution of the study lies in using a combination of GIS, AHP, and DEA for quantitatively assessing the CoF, firstly, the criteria weights are determined by the AHP method through experts’ judgments. Then, GIS functionalities along with DEA, are used to calculate scores for the alternatives. Finally, the outputs of the AHP method are integrated with the outputs of the DEA method in order to calculate CoF. The proposed method is applied to a local sewer pipeline network as a real-world case study to assess its risk of failure. The results indicated that the sewer pipelines are in good condition in the study area and among 1605 sewer pipelines, only 48 of them (about 3 %) are in a critical situation that it is needed to perform rehabilitation program. © 2019 Institution of Chemical Engineers
Publication Date: 2019
ISPRS International Journal of Geo-Information (22209964)(12)
A comprehensive fire risk assessment is very important in dense urban areas as it provides an estimation of people at risk and property. Fire policy and mitigation strategies in developing countries are constrained by inadequate information, which is mainly due to a lack of capacity and resources for data collection, analysis, and modeling. In this research, we calculated the fire risk considering two aspects, urban infrastructure and the characteristics of a high-rise building for a dense urban area in Zanjan city. Since the resources for this purpose were rather limited, a variety of information was gathered and information fusion techniques were conducted by employing spatial analyses to produce fire risk maps. For this purpose, the spatial information produced using unmanned aerial vehicles (UAVs) and then attribute data (about 150 characteristics of each high-rise building) were gathered for each building. Finally, considering high-risk urban infrastructures, like the position of oil and gas pipes and electricity lines and the fire safety analysis of high-rise buildings, the vulnerability map for the area was prepared. The fire risk of each building was assessed and its risk level was identified. Results can help decision-makers, urban planners, emergency managers, and community organizations to plan for providing facilities and minimizing fire hazards and solve some related problems to reduce the fire risk. Moreover, the results of sensitivity analysis (SA) indicate that the social training factor is the most effective causative factor in the fire risk. © 2019 by the authors.
Publication Date: 2019
International Journal of Disaster Risk Reduction (22124209)
The paper proposes an alternative new approach in contrast with the traditional methods to deal with multi-criteria group decision-making problems. It takes into account the multi-criteria group decision-making process as a multi-stakeholder multi-issue negotiation problem, in which stakeholders attempt to lead a consensus on the relative importance of the criteria by using software agents. To do so, it suggests three main steps: pre-negotiation, automated negotiation, and evaluation phases. The pre-negotiation phase is a human-computer interaction by which software agents attempt to exhibit and model the preferences space of the stakeholders. In the automated negotiation phase, the agents come together to negotiate on the criteria weights to reach an agreement on behalf of the stakeholders. Finally, in the evaluation phase, the evaluator agent applies a sensitivity analysis method to determine output variations due to the inputs and parameters. The proposed method is applied to a disaster management practice as a real-world case study, in which some stakeholders jointly attempt to identify the strategic roads in disaster situations specifically, flood events. Three spatial criteria are used for evaluating the road transportation network: load capacity, access to emergency suppliers, and importance of the roads in geometric structure of the network. The results of the study confirm that the proposed method is an efficient alternative approach to deal with multi-criteria group decision-making problems. © 2019 Elsevier Ltd
Publication Date: 2019
Environmental Monitoring and Assessment (01676369)(6)
The water table is an important piece of data for hydrogeological studies, particularly as input data to groundwater simulation models. Since the accuracy of groundwater simulation models significantly depends on input data, this study highlights the application of fuzzy kriging to improve the accuracy of water table interpolation. The results of the fuzzy kriging approach are compared with common methods in water table interpolation like ordinary kriging, inverse distance weighting (IDW), and Thiessen polygon methods to justify the suitability of the fuzzy kriging. The Gilan and Zanjan plains, located in the northwest of Iran, are used as case study areas. The Gilan Plain is characterized by a dense and regular piezometric network and gentle hydraulic gradient. The longitudinal plain of Zanjan has a sparse and irregular piezometric network and steep hydraulic gradient. Since these plains have different piezometric network configurations, the sensitivity of the interpolation methods to the monitoring point configuration is analyzed. The cross-validation method is employed to validate the accuracy of interpolation methods in water table interpolation. In control points, the average of root-mean-square errors associated with groundwater water table values estimated using fuzzy kriging, ordinary kriging, IDW, and Thiessen polygon methods are obtained to be respectively 1.36, 1.93, 3.49, and 9.10 in the Gilan Plain and 13.60, 22.86, 32.30, and 59.81 in the Zanjan Plain. The results indicate that the fuzzy kriging technique has greater precision in comparison with other methods, especially under the conditions of the sparse piezometric network and steep hydraulic gradient. The results also demonstrate that the used methods generally have higher accuracy in the Gilan Plain with a regular piezometric network than in the Zanjan Plain. Furthermore, Thiessen polygon, IDW, and ordinary kriging methods overestimated water table in comparison with the fuzzy kriging method in our cases. This overestimation may cause large error values in subsequent calculations such as water budget and aquifer storage which play a major role in the appropriate management of water resources. © 2019, Springer Nature Switzerland AG.
Publication Date: 2017
ISPRS International Journal of Geo-Information (22209964)(9)
Urban land-use allocation is a complicated problem due to the variety of land-uses, a large number of parcels, and different stakeholderswith diverse and conflicting interests. Various approaches and techniques have been proposed for the optimization of urban land-use allocation. The outputs of these approaches are almost optimum plans that suggest a unique, appropriate land-use for every land unit. However, because of some restrictions, such stakeholder opposition to a specific land-use or the high cost of land-use change, it is not possible for planners to propose a desirable land-use for each parcel. As a result, planners have to identify other priorities of the land-uses. Thus, ranking land-uses for parcels along with optimal land-use allocation could be advantageous in urban land-use planning. In this paper, a parcel-levelmodel is presented for ranking and allocating urban land-uses. The proposed model benefits from the capabilities of geographic information systems (GIS), fuzzy calculations, and Multi-Criteria Decision-Making (MCDM) methods (fuzzy TOPSIS), intends to improve the capabilities of existing urban land-use planning support systems. In this model, as a first step, using fuzzy calculations and spatial analysis capabilities of GIS, quantitative and qualitative evaluation criteria are estimated based on physical characteristics of the parcels and their neighborhoods. In the second step, through the fuzzy TOPSIS method, urban land-uses are ranked for each of the urban land units. In the third step, using the proposed land-use allocation process and genetic algorithm, the efficiency of the model is evaluated in urban land-use optimal allocation. The proposed model is tested on spatial data of region 7, district 1 of Tehran. The implementation results demonstrate that, in the study area, the land-use of 77.2% of the parcels have first priority. As such, the land-use of 22.8% of the parcels do not have first priority, and are prone to change. © 2017 by the Author.
Masoumi Z.,
Maleki, J.,
Mesgari, Mohammad Sadi,
Mansourian a., Publication Date: 2017
Geographical Analysis (00167363)(1)
Usually, allocation of resources is an optimization problem which involves a variety of conflicting economic, social, and ecological objectives. In such a process, advanced geographic analyst tool for manipulation of spatial data and satisfaction of multiple objectives is essential to the success of decision-making. The present research intends to demonstrate the application of a multiobjective optimization method based on NSGA-II (we call it HNSGA-II), along with Geographical Information System (GIS) to select suitable sites for the establishment of large industrial units. Having defined the elements of HNSGA-II for the site selection of industrial units, the method is tested on the data of Zanjan province, Iran, as the case study. The results showed that the proposed approach can easily find a variety of optimized solutions, giving the decision-makers the possibility to opt for the most propitious solution. Using this method, the achievement level regarding each objective function can be studied for any of the nondominated solutions. © 2016 The Ohio State University
Road accidents are one of the major causes of mortality around the world and over 1,300,000 people are killed annually in the road accidents. Most of fatal accidents occur on the roads outside the city. Some of the casualties are killed in the crash moment and the others after the accident, mostly due to late arrival of rescue groups. The late arrival of rescue groups is mostly because of the lack of rapid and timely notice from accident. For this reason, this paper proposes the employment of location-based service to develop a system that can be used easily to locate an accident more quickly and inform emergency service to accelerate the transfer of victims to medical centers. This system is composed of two parts. The first part of the system is activated when something hits the impact sensors embedded in the vehicle and then it captures the location of vehicle via GPS. Employing GSM, the first part of the system sends an SMS which contains the location and other necessary information of vehicle to the second part of system which is situated in the emergency center. After the SMS is delivered, the system is able to locate the accident on the map and dispatch the rescue groups to the place of accident. © Gi4DM 2011 - GeoInformation for Disaster Management.All right reserved.
Regarding the complexity of natural disasters in cities and the urgent need to employ methods in order to reduce the risk in residential areas, the risk management as a new and effective method in preventing and preparation for critical situations, has been employed in different ways throughout the world. Risk management includes a set of processes needed for identification, analysis and reaction against the crisis that aims at maximization of desired goals and minimization of risks and adverse consequences. This paper intends to present a GIS-based fuzzy approach for risk assessment in residential areas. Places such as medical centers and parks are effective factors in reducing the risk and the gas stations and high voltage power stations are factors that increase the risk. Now regarding the distance between each urban feature and the above features, fuzzy linguistic variables are defined and according to the rules extracted by expert, the risk of each feature is separately estimated and designed as a risk map for each area. Now with the help of this map, we can reduce the risk to which every building is subjected by constructing the needed centers and also fortification plans. © Gi4DM 2011 - GeoInformation for Disaster Management.All right reserved.
Rahmani m., M.,
Asgari, J.,
Asgarimehr, M.,
Wickert, J. Publication Date: 2025
Journal of Geophysical Research: Biogeosciences (21698953)130(3)
Accurately characterizing the impact of vegetation and roughness on CYGNSS observations, which are two main sources of disturbance, is essential for achieving high-quality estimates of soil moisture through this mission. While there are several ancillary data sets that can be employed to address vegetation influence, the lack of a global data set for soil surface roughness motivates us to globally map the contribution of soil roughness to CYGNSS observations. To accomplish this, since separating the contribution of surface roughness and vegetation on reflected signals is often challenging, we initially integrate the vegetation and roughness contributions into a unique variable, denoted as VR. Next, the impacts of vegetation integrated into the CYGNSS-derived VR were separated using Leaf Area Index to map the roughness parameter Hr. The mean value of Hr obtained in this research through CYGNSS observations ranges from 3.2 to 4.6. We observed that the spatial distribution of Hr values is influenced by the predominant vegetation types, with forests exhibiting higher roughness values (Hr = 4.47–4.67), while deserts, shrubs, crops, and bare soils exhibit the smallest Hr values (Hr = 3.25–3.36). Furthermore, we inferred vegetation optical depth (VOD) through CYGNSS observations in conjunction with estimated Hr values. The good agreement observed between the estimated VOD in this study and other vegetation indices, including Vegetation Water Content and tree height, highlights the effectiveness of the introduced Hr global data set in our research and its promising potential in the future GNSS-R studies. © 2025. American Geophysical Union. All Rights Reserved.
Publication Date: 2024
Journal of Surveying Engineering (07339453)150(1)
Multipath is a limiting factor for accurate positioning by global navigation satellite system (GNSS). Different hardware and computational techniques have been proposed for its mitigation. Here a geometrical approach for multipath localization and mitigation is presented: localization is performed by ray-tracing and mitigation by analyzing the residuals of ambiguity resolved precise point positioning. The main advantages of the method are its ability to correct nearly the multipath-affected parts of raw data and its relative independence of observation duration (e.g., more than 1 h). The method is based on a ray-tracing algorithm and is applicable to all GNSS constellations. It is independent of physical properties of reflecting surfaces, receiver/antenna type and observation sampling rate. The methodology was implemented on static real global positioning system (GPS) data acquired during six consecutive days in presence and in absence of a metallic reflecting plate. The analysis was performed on two kinds of data series: observations residuals and epoch-wise coordinates. The overall RMSs of observations residuals were reduced by 55% on average. The RMS of easting, northing, and elevation residual time series resulting from affected observations were 8.1 mm, 13.3 mm, and 23.8 mm, respectively; while they were reduced to 6.9 mm, 9.7 mm, and 22.4 mm after correction (22% improvement in horizontal and a minor improvement in vertical components). © 2023 American Society of Civil Engineers.
Publication Date: 2023
Journal of Hydrology: Regional Studies (22145818)50
Study region: The Kabudarahang Plain and the Razan-Qahavand Plain. Study focus: Improper use of water resources has reduced groundwater levels and created land subsidence (LS) in many plains of Iran. The aim and innovation of this research are to study multi-sensor observations for LS and groundwater depletion and explore the relationships of the involved variables with high confidence. The gravity recovery and climate experiment (GRACE) observations can be used to evaluate water storage changes at the Earth's surface. GRACE has stripe errors, leakage and various noises that multilevel 3D wavelet decomposition (M3WD) has been suggested to mitigate noises and downscale for small scale. This study has investigated the interferometric synthetic-aperture radar (InSAR) of Sentinel-1 images from October 2014 to September 2019, the GRACE data from March 2002 to July 2016, and groundwater hydrograph (GH) from 2014 to 2020. New hydrological insight for the region: The maximum LS rate, obtained from small baseline subset-differential of InSAR is 20 mm/year at the Kabudarahang Plain (KP) and 30 mm/year at Razan-Qahavand Plain (RQP). The groundwater storage variations (ΔGW) have a decreasing trend of 78.45 ± 0.2 million cubic meters/year. The GH for the KP and RQP shows a downward trend of 3.25 and 1.81 m/year, respectively. Based on the outcomes, the M3WD can increase the correlation of ΔGW with other sensors by 15 %. Also, validation between sensors with normalized cross-correlation has remarkable compatibility. The multi-sensor study of ΔGW and LS revealed various dimensions with high reliability and can facilitate the water resource management. © 2023 The Authors
Publication Date: 2023
Meteorological Applications (13504827)30(6)
The weighted mean temperature ((Formula presented.)) plays a crucial role in calculating Precipitable Water Vapor (PWV) and integrated water vapor (IWV) using Global Navigation Satellite Systems (GNSS) techniques. Currently, the primary sources for meteorological parameters are radiosonde measurements and Numerical Weather Models (NWMs). This study focuses on assessing the influence of different data sources on the computation of (Formula presented.) and IWV in Iran. The investigation involved comparing several datasets: ERA5 numerical data with spatial resolutions of 0.125° and 2.5° (ERA5 0.125, ERA5 2.5), ERA-Interim, NCEP numerical data and (Formula presented.) results derived from the GPT3 model. Validation of the results utilized data from 12 radiosonde stations situated across Iran. In addition, the precision of the IWV parameter was evaluated by utilizing measurements from the only available IGS station in the region, situated in Tehran. The results revealed that ERA5 0.125 exhibited superior accuracy in (Formula presented.) estimation compared with the other datasets, showing a discrepancy of approximately 1–2 K. In contrast, the GPT3 model displayed an accuracy of about 3 K. Analysing the results across different months of the year revealed elevated root mean square error (RMSE) values during warmer months, with little variability based on station height in the region for the four datasets. Regarding IWV, the ERA5 0.125 dataset outperformed the other three datasets, demonstrating an accuracy of about 0.07 kg m−2. Notably, RMSE values during summer were approximately 50% higher compared with the annual RMSE. © 2023 The Authors. Meteorological Applications published by John Wiley & Sons Ltd on behalf of Royal Meteorological Society.
Publication Date: 2023
Natural Resources Research (15207439)32(3)pp. 1007-1020
Improper abstraction of groundwater in Iran has led to an average annual subsidence rate of 15 cm/yr. The management of Iran's water resources is essential due to its arid and semiarid climate and traditional agriculture. Monitoring groundwater storage (GWS) changes and their correct interpretation using deep learning (DL) methods can improve our understanding of groundwater systems. For this purpose, in this study, the GWS in Iran from 2003 to 2021 was downscaled using DL based on combining gravity recovery and climate experiment (GRACE) and GRACE-Follow on with a hydrological model. The GWS downscaling was performed from 1° to 0.25°. The GWS in the south of Tehran and northeast of Qazvin had the highest decrease of 15 mm/yr. A new GWS index was developed to correctly interpret the decline in GWS through the standardized precipitation index. The main reason for the decrease in GWS was the development of unsustainable agriculture from 2007 to 2012, which reached its lowest possible level after 2012–2018 with the intensification of climatic conditions. The calculated GWS index correlates more than 80% with 400 piezometric wells in Iran. © 2023, International Association for Mathematical Geosciences.
Mirmohammadian, F.,
Asgari, J.,
Verhagen, S.,
Amiri-simkooei, A. Publication Date: 2022
Sensors (14248220)22(15)
Until now, RTK (real-time kinematic) and NRTK (Network-based RTK) have been the most popular cm-level accurate positioning approaches based on Global Navigation Satellite System (GNSS) signals in real-time. The tropospheric delay is a major source of RTK errors, especially for medium and long baselines. This source of error is difficult to quantify due to its reliance on highly variable atmospheric humidity. In this paper, we use the NRTK approach to estimate double-differenced zenith tropospheric delays alongside ambiguities and positions based on a complete set of multi-GNSS data in a sample 6-station network in Europe. The ZTD files published by IGS were used to validate the estimated ZTDs. The results confirmed a good agreement, with an average Root Mean Squares Error (RMSE) of about 12 mm. Although multiplying the unknowns makes the mathematical model less reliable in correctly fixing integer ambiguities, adding a priori interpolated ZTD as quasi-observations can improve positioning accuracy and Integer Ambiguity Resolution (IAR) performance. In this work, weighted least-squares (WLS) were performed using the interpolation of ZTD values of near reference stations of the IGS network. When using a well-known Kriging interpolation, the weights depend on the semivariogram, and a higher network density is required to obtain the correct covariance function. Hence, we used a simple interpolation strategy, which minimized the impact of altitude variability within the network. Compared to standard RTK where ZTD is assumed to be unknown, this technique improves the positioning accuracy by about 50%. It also increased the success rate for IAR by nearly 1. © 2022 by the authors.
Publication Date: 2022
Acta Geophysica (18956572)70(3)pp. 1445-1454
Weighted mean temperature (Tm) is used to determine water vapor content, precipitable water vapor, and integrated water vapor (IWV) in GNSS. This parameter is highly correlated with climate conditions as well as the type of the region. The case study is performed in Iran which has diverse climate. ERA5 reanalysis datasets were used at a compact grid of 0.125 × 0.125 between 2007 and the end of 2019 to model the Tm. The data obtained from 12 radiosonde stations along with an IGS station located in Tehran were employed in this research. Five models were examined for Tm. Bevis model, linear grouping model (LGM), and linear nearest grid point model (LNGPM) were considered as Tm linear models, and harmonic model (HM) and GPT2w model were used as nonlinear models. In LGM method the study region was divided into smaller areas with different linear model coefficients using spatial grouping method. The local model in each radiosonde station was considered as a reference. According to the results, the accuracy of linear models (Bevis and LGM model) was between 3 and 8 K (radiosonde data as reference); also 7 out of 12 stations in the LGM had higher accuracy than the Bevis model (based on RMSE). The accuracy of the two GPT2w models and the harmonic model was higher than the previous two models, and it was between 2 and 4 K. The IWV values were obtained using zenith total delay observations of IGS station located in Tehran using 5 models and were compared with the IWV values of the radiosonde station. The accuracy of the values in three linear models, Bevis, LGM, and LNGPM, was, respectively, 0.2, 0.17, and 0.14 kg m−2, and in the two nonlinear models, GPT2w and HM, was 0.13 kg m−2. © 2022, The Author(s) under exclusive licence to Institute of Geophysics, Polish Academy of Sciences & Polish Academy of Sciences.
Publication Date: 2022
International Journal of Remote Sensing (01431161)43(14)pp. 5173-5203
Accurate knowledge of soil moisture is critical for hydrological and agricultural applications such as agricultural irrigation management, drought characterization, and flood detection. Researchers have attempted to provide soil moisture using various methods and techniques. Traditionally, the amount of soil moisture was based on field measurements. On the other hand, remote sensing satellites have been widely used to provide continuous soil moisture measurements worldwide, encountering problems such as the lack of simultaneous spatial and temporal sampling rates and dependence on weather conditions. However, in recent decades, GNSS signals reflected from the Earth’s surface (GNSS-R technique) have been increasingly used for soil moisture monitoring, due to the numerous advantages it offers. This paper aims to provide a comprehensive review of soil moisture retrieved by two space-based GNSS-R missions (TDS-1 and CYGNSS) to show the general past trends, gaps, and opportunities for soil moisture monitoring through GNSS-R observations. © 2022 Informa UK Limited, trading as Taylor & Francis Group.
Publication Date: 2022
Marine Georesources and Geotechnology (1064119X)40(3)pp. 361-369
Lake Urmia is located in the northwest of Iran and shared between the provinces of West Azarbaijan and East Azarbaijan. In the last two decades, there has been a considerable decline in the lake’s water level. Satellite altimetry (SA) together with the advanced precise orbital positioning system has reached a high accuracy in the measurement of the water level height, but increasing the accuracy of waveform retracking (WR) is a challenging issue. In this study, wavelet decomposition and convolutional neural network were used for the WR with 50%, 55%, and 60% training scenarios and the threshold method was used for the 1992–2019 period. The training of 55% has the best result with a ± 0.027 m root mean square error. The water level has decreased by approximately 7 m from 1994 to 2018 and its overall trend is downward. The proposed method has been able to increase the WR accuracy by up to 30%. The gravity recovery and climate experiment and the annual monitoring of the water level station have also been used for the SA verification, which have a significant correlation of 0.66 and 0.96 with SA, respectively. © 2021 Informa UK Limited, trading as Taylor & Francis Group.
Mirmohammadian, F.,
Asgari, J.,
Verhagen, S.,
Amiri-simkooei, A. Publication Date: 2022
Remote Sensing (20724292)14(1)
With the advancement of multi-constellation and multi-frequency global navigation satellite systems (GNSSs), more observations are available for high precision positioning applications. Although there is a lot of progress in the GNSS world, achieving realistic precision of the solution (neither too optimistic nor too pessimistic) is still an open problem. Weighting among different GNSS systems requires a realistic stochastic model for all observations to achieve the best linear unbiased estimation (BLUE) of unknown parameters in multi-GNSS data processing mode. In addition, the correct integer ambiguity resolution (IAR) becomes crucial in shortening the Time-To-Fix (TTF) in RTK, especially in challenging environmental conditions. In general, it is required to estimate various variances for observation types, consider the correlation between different observables, and compensate for the satellite elevation dependence of the observable precision. Quality control of GNSS signals, such as GPS, GLONASS, Galileo, and BeiDou can be performed by processing a zero or short baseline double difference pseudorange and carrier phase observations using the least-squares variance component estimation (LS-VCE). The efficacy of this method is investigated using real multi-GNSS data sets collected by the Trimble NETR9, SEPT POLARX5, and LEICA GR30 receivers. The results show that the standard deviation of observations depends on the system and the observable type in which a particular receiver could have the best performance. We also note that the estimated variances and correlations among different observations are also dependent on the receiver type. It is because the approaches utilized for the recovery techniques differ from one type of receiver to another kind. The reliability of IAR will improve if a realistic stochastic model is applied in single or multi-GNSS data processing. According to the results, for the data sets considered, a realistic stochastic model can increase the computed empirical success rate to 100% in multi-GNSS as well as a single system. As mentioned previously, the realistic precision of the solution can be achieved with a realistic stochastic model. However, using the estimated stochastic model, in fact, leads to better precision and accuracy for the estimated baseline components, up to 39% in multi-GNSS. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
Publication Date: 2022
Survey Review (00396265)54(385)pp. 349-362
The NUVEL1-A is one of the old and popular plate tectonic models. While the NUVEL1-A is a geological-based model, recently a model has been proposed (GSRM2.1 model) which is based on the results of space geodetic techniques. In this work, we investigate the consistency of these models with the VLBI and SLR results in Europe. Direction and magnitude of the horizontal motion from NUVEL-1A and GSRM2.1 models are compared with corresponding values from both geodetic techniques. This comparison provides valuable deductions such as: (1) The values of geodetic-based model (GSRM2.1) show better agreement with SLR and VLBI results (2) In each comparison between geodetic results and modelled values, direction divergence is larger than magnitude difference. © 2021 Survey Review Ltd.
Publication Date: 2021
Remote Sensing Letters (2150704X)12(5)pp. 499-509
Monitoring the melting of Greenland ice using various sensors is of great importance due to global sea level rise. The mass changes in Greenland can be observed with the GRACE (Gravity Recovery and Climate Experiment) mission from 2002 to 2016. The GRACE limitations and noise are due to the geometrical and instrumental properties along its orbit, which requires investigations for further improvement. The innovation of this research is to introduce a new method in four-dimensional (4D) wavelet decomposition (WD) for increasing the efficiency of the GRACE signal, used for the reconstruction of the Greenland mass changes. The results show that the overall downward trend in the west Greenland coast is 25.25 ± 6.95 cm/year, and the highest decline rate is 33.60 ± 6.23 cm/year from 2013 to 2016. The northern regions of Greenland have less mass loss than the west and south. For verification, the 4D WD output has been compared with the CryoSat-2 results from 2011 to 2016. The GRACE and CryoSat-2 show a significant correlation of 0.62, which indicates an improvement of 0.18 compared to the forward modelling. The 4D WD improves the overall performance of the reconstructed signal in the frequency time-space domain and reduces the noise in each dimension. © 2021 Informa UK Limited, trading as Taylor & Francis Group.
Amiri-simkooei, A.,
Hosseini-asl m., ,
Asgari, J.,
Zangeneh-nejad f., F. Publication Date: 2019
GPS Solutions (10805370)23(1)
Proper analysis and subsequent interpretation of GPS position time series is an important issue in many geodetic and geophysical applications. The GPS position time series can possibly be contaminated by some abrupt changes, called offsets, which can be well compensated for in the functional model. An appropriate offset detection method requires proper specification of both functional and stochastic models of the series. Ignoring colored noise will degrade the performance of the offset detection algorithm. We first introduce the univariate analysis to identify possible offsets in a single time series. To enhance the detection ability, we then introduce the multivariate analysis, which considers the three coordinate components, north, east and up, simultaneously. To test the performance of the proposed algorithm, we use synthetic daily time series of three coordinate components emulating real GPS time series. They consist of a linear trend, seasonal periodic signals, offsets and white plus colored noise. The average detection power on individual components, either north, east or up, are 32.3 and 47.2% for the cases of white noise only and white plus flicker noise, respectively. The detection power of the multivariate analysis increases to 70.8 and 87.1% for the above two cases. This indicates that ignoring flicker noise, existing in the structure of the time series, leads to lower offset detection performance. It also indicates that the multivariate analysis is more efficient than the univariate analysis for offset detection in the sense that the three coordinate component time series are simultaneously used in the offset detection procedure. © 2018, Springer-Verlag GmbH Germany, part of Springer Nature.
